| Course title | Unstructured data processing |
|---|---|
| Course code | USII/KZND |
| Organizational form of instruction | Lecture |
| Level of course | Master |
| Year of study | 1 |
| Semester | Summer |
| Number of ECTS credits | 4 |
| Language of instruction | Czech |
| Status of course | Compulsory-optional |
| Form of instruction | Face-to-face |
| Work placements | This is not an internship |
| Recommended optional programme components | None |
| Lecturer(s) |
|---|
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| Course content |
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The role and specifics of unstructured data Possibilies of inverted index design Dictionary-based models Statistical approaches to unstructured data extraction Relation extraction from unstructured data Semantic annotation and ontologies Visual and text information extraction from images Models for information retrieval from images Models for automatic speech recognition Evaluation of quality of unstructured data processing
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| Learning activities and teaching methods |
| Monologic (reading, lecture, briefing), Dialogic (discussion, interview, brainstorming), Work with text (with textbook, with book), Methods of individual activities, Laboratory work |
| Learning outcomes |
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The subject aims to develop a general understanding of the fundamental methods for unstructured data processing, in particular text documents, image and audio data. This processing leads to structured or at least semi-structured data. This enables further analyses, including data visualisation and knowledge discovery.
Students will be capable of understanding both theoretical and practical aspects of unstructured data processing and information retrieval in these data. They will also be able of designing systems for automatic unstructured data processing. |
| Prerequisites |
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Basic skills in PC and MS Excel utilization.
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| Assessment methods and criteria |
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Oral examination, Systematic monitoring
Assignment: successful elaboration of given tasks with 60% at minimum. Successful defense of a practical project that cover theoretical knowledge gained within this course and includes a design of system for automatic processing of selected set of unstructured data. Examination: oral examination. Detailed information will be provided during the first lecture and in Stag. |
| Recommended literature |
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| Study plans that include the course |
| Faculty | Study plan (Version) | Category of Branch/Specialization | Recommended semester | |
|---|---|---|---|---|
| Faculty: Faculty of Economics and Administration | Study plan (Version): Informatics in Public Administration (2014) | Category: Economy | 1 | Recommended year of study:1, Recommended semester: Summer |